Mohamed Nasser

Robotics AI Engineer | Generative AI on Edge | ROS 2 | Computer Vision | Autonomous Systems

Building intelligent autonomous systems at the intersection of generative AI and robotics — deploying edge AI that thinks and acts in real time.

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Background

About Me

Results-driven Mechatronics Engineer with hands-on expertise in AI, Computer Vision, and Autonomous Systems. I deliver production-ready solutions — from a full-stack delivery robot with 23-package ROS 2 architecture to real-time driver monitoring with 99.8% accuracy.

Passionate about bridging the gap between AI research and real-world robotics, with a particular focus on generative AI on edge devices and multi-agent autonomous systems.

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Robotics
ROS 2, Nav2, SLAM

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Generative AI
LLMs, GANs, RAG

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Computer Vision
YOLOv8, MediaPipe

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Edge Deployment
ONNX, TFLite, Pi 4

B.Sc. Mechatronics Engineering

Higher Technological Institute (HTI)

GPA 3.44 / 4.0 — Excellent

Graduation Project: Autonomous Indoor Delivery Robot — Excellent
Generative AI on Edge Devices
ROS 2 & Autonomous Navigation
Real-time Computer Vision
Embedded Systems & IoT

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Work History

Professional Experience

AI & Data Science Trainee

Digital Egypt Pioneers Initiative (DEPI)

12/2025 — Present

Generative AI LLMs GANs Transformers RAG NLP

Specialized in Generative AI: built 3+ end-to-end pipelines using GANs, LLMs, and Transformers for production deployment
Attained 85%+ average accuracy across NLP classification and Computer Vision tasks on 10K+ samples
Developing capstone: RAG-powered Q&A system with custom attention mechanisms processing 8K+ domain-specific documents

AI Engineering Trainee

Summit Technology Solutions

08/2025 — 01/2026

YOLOv8 MediaPipe InsightFace ONNX Computer Vision Edge AI

Built real-time Driver Monitoring System using YOLO, InsightFace, and MediaPipe — 99.8% accuracy detecting 15+ safety events across 2,000+ test scenarios
Implemented Arabic Sign Language Translator using MediaPipe, Autoencoders, and CTC decoding — 120+ signs at 30 FPS with 94% accuracy
Achieved 45ms inference latency on CPU/edge with 80% false-alert reduction through quantized ONNX models

Selected Work

Featured Projects

01 — ROBOTICS / GRADUATION PROJECT

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Autonomous Indoor Delivery Robot

Full-stack logistics robot — 23-package ROS 2 system with Nav2 & SLAM. 95% obstacle avoidance, QR authentication, bilingual voice assistant "Rafiq" (Llama.cpp + Whisper) on Raspberry Pi 4.

ROS 2 Nav2 SLAM YOLOv8 Llama.cpp Whisper Streamlit Android

Project Gallery — 16 Photos